Stimulus Verification is a Universal and Effective Sampler in Multi-modal Human Trajectory Prediction-Reference-Cited by-同舟云学术

Stimulus Verification is a Universal and Effective Sampler in Multi-modal Human Trajectory Prediction

Published:2023-06 Issue: Volume: Page:
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Container-title:2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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Author:

Sun Jianhua¹,Li Yuxuan¹,Chai Liang¹,Lu Cewu²

Affiliation:

1. Shanghai Jiao Tong University,China

2. Qing Yuan Research Institute, AI Institute, Shanghai Jiao Tong University,MoE Key Lab of Artificial Intelligence,China

Funder

National Key Research and Development Project of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10203037/10203050/10203823.pdf?arnumber=10203823

Reference48 articles.

1. Improved variational inference with inverse autoregressive flow;kingma;Advances in neural information processing systems,2016

2. Sgcn: Sparse graph convolution network for pedestrian trajectory prediction;shi;Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition,0

3. Dynamic filter networks;jia;Advances in neural information processing systems,2016

4. Trajectron++: Dynamically-feasible trajec-tory forecasting with heterogeneous data;salzmann;European Conference on Computer Vision,0

5. Social-bigat: Multimodal trajectory forecasting using bicycle-gan and graph attention networks;kosaraju;Advances in neural information processing systems,2019

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